Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
GeoMFormer: A General Architecture for Geometric Molecular Representation Learning
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2406.16853.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-09T16:26:03.466879Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T21:57:43.095437Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 30145f5d-6635-44c4-b797-5efec871be62 · inbound
Efficient and Scalable Density Functional Theory Hamiltonian Prediction through Adaptive Sparsity cites this paper.
Efficient and Scalable Density Functional Theory Hamiltonian Prediction through Adaptive Sparsity GeoMFormer: A General Architecture for Geometric Molecular Representation Learning
Reference 2000
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T16:26:03.466879Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9e47ef2c-13aa-45fb-9e74-a51b32e410eb · inbound
A Benchmark for Quantum Chemistry Relaxations via Machine Learning Interatomic Potentials cites this paper.
A Benchmark for Quantum Chemistry Relaxations via Machine Learning Interatomic Potentials GeoMFormer: A General Architecture for Geometric Molecular Representation Learning
Reference 11
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T21:57:43.259116Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.